Synthesize Neural Sliding Mode Controller for Nonlinear System
نویسندگان
چکیده
In this paper, we will propose a cooperative control approach that is based on the Synthesize of self-tuning neural network with sliding mode control methodology. The main purpose is to eliminate the chattering phenomenon such that the seesaw system has a superior fixed position and tracking response. Moreover, the system performance obtained via the method of synthesize neural network with SMC (SNNS) can be improved. In the present approach, two parallel Neural Networks are utilized to realize a Neuro-Sliding Mode Control. The equivalent control and the corrective control in terms of sliding mode control are the outputs of the Neural Networks. The weights adaptations of Neural Network are determined based on the sliding mode control equations. The simulation and experiment seesaw system result show which the proposed controller shown that the proposed method is feasible and effective. Key-Words: Neural Network, Sliding mode control, Seesaw
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